|Tutorial A||Network Function Virtualization: Conception, Present and Future||
|Tutorial B||Computational Intelligence Computational Intelligence Methods for Optimization||Tortonesi Mauro||4/29/2016 AM|
|Tutorial C||Big Data for Networking: Objectives, Challenges and Applications||Zeydan Engin||4/29/2016 PM|
|Tutorial D||Optimization of Smart Grid Design, Operations, and Management||
Network Function Virtualization: Conception, Present and Future
This tutorial will discuss NFV from its conception, through the various proof of concepts, to the challenges that are slowing commercial deployments. We will also have a demo on SDN-based service function chaining, as well as hands-on experience involving deploying, testing and scaling a virtualized IP Multimedia Subsystem on OpenStack.
Rashid Mijumbi obtained a degree in electrical engineering from Makerere University, Uganda in 2009, and a PhD in telecommunications engineering from the Universitat Politecnica de Catalunya (UPC), Spain in 2014. He is currently a Postdoctoral Researcher in the Telecommunications Systems and Software Group (TSSG) at Waterford Institute of Technology (WIT). His research interests are in autonomic management of networks and services. Current focus is on management of resources for virtualized networks and functions, cloud computing and software defined networks. He has participated in a number of competitively funded European and Spanish national projects in this area including the ongoing Flamingo EU Project. He is also on the technical program committees of leading Conferences as well as a regular reviewer for Journals in the area of network and service management.
Niels Bouten obtained a masters degree in computer science from Ghent University, Belgium, in June 2011. In August 2011, he joined the Department of Information Technology at Ghent University, where he is active as a Ph.D. student. His main research interests are the application of autonomic network management approaches in multimedia delivery. The focus of this research is mainly on the end-to-end Quality of Experience optimization, ranging from the design of a single autonomic control loop to the federated management of these distributed loops. He is currently participating in the Flamingo EU Project.
Computational Intelligence Computational Intelligence Methods for Optimization
This tutorial will introduce computational intelligence methods, that represent a very promising optimization approach in network and system management research. More specifically, the tutorial will focus on population-based metaheuristics such as Genetic Algorithms, Particle Swarm Optimization, and Clonal Selection Algorithm, that are very well suited for the optimization of dynamic, non-smooth, and computationally expensive target functions. Those techniques can be effectively used for a wide range of research applications in network and service management and are especially interesting for the optimization of systems not operating in steady-state and/or in case simulative approaches are adopted for the evaluation of system behavior.
Mauro Tortonesi graduated from the University of Ferrara, Italy, where he received a Ph.D. degree in computer engineering in 2006. He is an assistant professor at the Engineering Department of the University of Ferrara. Dr. Tortonesi's scientific work could be broadly classified along 4 main research activities: methodologies and tools for the modeling and optimization of support organizations for the resolution of incidents in the IT industry; business-driven methodologies and tools for the placement optimization of software components of complex IT services in federated Cloud environments; Internet-of-Things (IoT) management in industrial and military environments; methodologies and tools to support communications in extremely dynamic wireless environments such as mobile ad-hoc, delay-tolerant, opportunistic, and tactical edge networks.
Big Data for Networking: Objectives, Challenges and Applications
The objective of this tutorial is to introduce recent developments in networking technologies that are using big data ecosystem (Hadoop, MapReduce, HDFS, Hive, Spark, etc), discuss about challenges involved in big data networking and give some use case examples of usage of big data analytic techniques for mobile operators. In addition to discussing about general overview of big data ecosystem, the potential of big data analytics in decision making, operations optimization and new source of revenue generations are highlighted especially in the context of mobile operator ecosystem.
Engin Zeydan received the PhD degree in February 2011 from the Department of Electrical and Computer Engineering at Stevens Institute of Technology, Hoboken, NJ, USA. Previously, he received his M.S. and B.S. degrees from the Department of Electrical and Electronics Engineering at Middle East Technical University, Ankara, Turkey, in 2006 and 2004, respectively. Dr. Engin Zeydan has worked as an R&D engineer for Avea, a mobile operator in Turkey, between 2011 and 2016. He is currently with Türk Telekom Group working as an Innovation and Applied Research Engineer. His research interests are in the area of telecommunications and big data networking. Dr. Zeydan is a recipient of the Exemplary Reviewer for IEEE Communications Letters Award, 2011. Engin Zeydan is primarily responsible for carrying out European Commission and nationally funded research activities at Türk Telekom Group.
Optimization of Smart Grid Design, Operations, and Management
The overarching goal of this tutorial is to present the emerging optimization problems and formulations for the operations, design, and management of the Smart Grid from the communications and networking perspectives. We provide optimization formulations for various problems from generation of the electricity to its consumption, spanning scheduling, communications and control that are in dire need of development as part of the worldwide initiatives to upgrade the current power grid.
Suleyman Uludag received his Ph.D. from DePaul University, Chicago in 2007. He is an associate professor of computer science at the University of Michigan - Flint. The general areas of his research include smart grid security, privacy, and optimization, network quality of service, routing in wireless and wired networks, microgrids, network security, and smart grid data collection. He has co-chaired the IEEE LCN Workshop on Smart Grid Networking Infrastructure held in conjunction with IEEE LCN 2010 Conference in Denver, CO. He has been awarded the Lois Matz Rosen Junior Faculty Excellence in Teaching Award in September 2010 at the University of Michigan - Flint. He has been a Fulbright Scholar (Core Program) at TOBB University of Economics and Technology in Ankara, Turkey during the 2012-2013 academic year. He was a visiting scholar at the TCIPG (Trustworthy Cyber Infrastructure for the Power Grid) at the University of Illinois at Urbana-Champaign and the MONET research group of Professor Klara Nahrstedt at UIUC from August of 2013 to August of 2014. He has been an affiliated faculty at the Michigan Institute of Data Science (MIDAS) at the University of Michigan – Ann Arbor since February 2016.
Tolga Girici received his Ph.D. degree from University of Maryland, College Park USA in 2007. He is an associate professor of Electrical and Electronics Engineering at TOBB University of Economics and Technology, Ankara Turkey. He has previously worked as an Intern at Intellegent Automation Inc. at Bethesda MD, and Fujitsu Labs, College Park, MD USA. He has served in the TPC of many networking conferences such as ICC, Globecom, PIMRC and WCNC, and reviewer for many networking journals. His research interests include Next Generation Wireless Communications, LTE, Wireless Ad Hoc Networks and Tactical Communications. He has several journal and conference papers that utilize convex, linear, nonlinear and integer programming techniques for resource allocation in wireless networks. He has a Career Award from Turkish Scientific and Technological Council and several collaborations with industry. He received a best paper award in the MAC Track in the WICOM 2010 conference. Since November 2007, he gave around 30 courses at TOBB ETU, which includes Undergraduate and Graduate courses.
Bulent Tavli is currently an associate professor at the Electrical & Electronics Engineering Department, TOBB University of Economics and Technology, Ankara, Turkey. He received the B.Sc. degree in Electrical & Electronics Engineering in 1996 from the Middle East Technical University, Ankara, Turkey. He received the M.Sc. and Ph.D. degrees in Electrical & Computer Engineering in 2001 and 2005 from the University of Rochester, Rochester, NY, USA. Smart grid, information security, telecommunications, mathematical programming, and embedded systems are his current research areas.
Hakan Gultekin is an associate professor at the Department of Industrial Engineering, TOBB University of Economics and Technology (TOBB ETU) in Ankara, Turkey. He received his B.S., M.S. and Ph.D. degrees in Industrial Engineering from Bilkent University in Turkey. Before joining TOBB ETU he visited the University of Liege in Belgium for postdoctoral studies. His research interests include scheduling, optimization modeling and exact and heuristic algorithm development especially for the problems arising in modern manufacturing systems, wireless sensor networks and energy management. He has several journal and conference papers on these topics. He gave more than 30 courses both at the graduate and undergraduate levels at TOBB ETU on topics including Operations Research, Scheduling, Quantitative Decision Making Methods, Facilities Design and Planning, and Engineering Economy. He has a Career Project Award and a Project Performance Award both from the Scientific and Technological Research Council of Turkey (TUBITAK).